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The main implementation steps used in this type of system are face detection and recognizing the detected face.This paper proposes a model for implementing an automated attendance management system for students of a class by making use of face recognition technique, by using Eigenface values, Principle Component Analysis (PCA) and Convolutional Neural Network (CNN). This can greatly enhance the usability of Leap Motion. Finally, the images are divided into 5 types by the serious degree of diabetic retinopathy. Reference Paper IEEE 2019 Finger Vein Identification Based On Transfer Learning of AlexNet Published in: 2018 7th International Conference on Computer and Communication Engineering (ICCCE) https://ieeexplore.ieee.org/document/8539256. Between the years 2006 and 2014, Indian economy lost $340 billion(USD) due to TB. … “Olivia” is a Virtual Assistant developed specifically for homes, which can be integrated into any home to make it a Smart Home. Our system is mainly designed for edible objects like fruits and vegetables. We fuse the feature maps of two convolutional layers by using the operation of max-pooling to give input to the fully connected neural network layer. Reference Paper IEEE 2019A Method for Localizing the Eye Pupil for Point-of-Gaze EstimationPublished in: IEEE Potentials ( Volume: 38 , Issue: 1 , Jan.-Feb. 2019 )https://ieeexplore.ieee.org/document/8595416. Morphological processing is performed to remove the shadow from the image. Flow can identify millions of products like DVDs and CDs, book covers, video games, and packaged household goods – for example, the box of your favorite cereal. Finally, an efficient CNN with asymmetric kernels is used to be the classifier of traffic signs. Face Recognition using Image Processing for Visually Challenged In this paper the face recognition is done for the visually challenged people. However, face recognition performance is greatly influenced by the factors, such as facial expression, illumination, and pose changes. Image Classification with CIFAR-10 Dataset Deep Learning Project Idea – The CIFAR-10 dataset is a collection of images of 10 different classes like cars, birds, dogs, horses, ships, trucks, etc. Search results may include related images, sites that contain the image, as well as sizes of the image you searched for. Raspberry Pi Setup. There are two major techniques available to detect hand motion or gesture such as vision and non-vision technique and convert the detected information into voice through raspberry pi. OpenCV Image Processing Projects. We performed experiments with a dataset comprising 100 classes, averaging 1000 images for each class to acquire top 1 classification rate of up to 85%. Reference Paper IEEE 2019Shadow detection and removal from images using machine learning and morphological operationsPublished in: The Journal of Engineering ( Volume: 2019 , Issue: 1 , 1 2019 )https://ieeexplore.ieee.org/document/8627060. It works just like Google Images reverse search by offering users links to pages, Wikipedia articles, and other relevant resources connected to the image. Therefore, in this paper, we propose a DCNN structure named as D-Net. The main role of ANPR, in the application, is to extract the characters of a vehicle license number plate from an image. This is known as the eye fix or point of fixation. In order to test the accuracy and enhance the robustness of the model, we use Fruits-360 dataset which contains 55244 images spread across 81 classes. Reference Paper IEEE 2019 Kinect-Based Platform for Movement Monitoring and Fall-Detection of Elderly People Published in: 2019 12th International Conference on Measurement https://ieeexplore.ieee.org/document/8780004. Reference Paper IEEE 2019Deep Learning for Logo DetectionPublished in: 2019 42nd International Conference on Telecommunications and Signal Processing (TSP)https://ieeexplore.ieee.org/document/8769038. Modern artificial neural networks are able to detect and localize objects of known classes. The experimental part addressed the finding of the optimum values for template and image source dimension, as well as the scaling factor. The method is developed to be applicable in real time on a low-cost embedded system for indoor service robots. We tried to fix this problem using the key download method. The main contribution of this paper is the development of an expert system tool for evaluating the ripeness of banana fruit. In this research, we focused finger vein identification system by using our own finger vein dataset, we trained it with transfer learning of AlexNet model and verified by test images. A computer-aided diagnosis (CAD) system based on mammograms enables early breast cancer detection, diagnosis, and treatment. Reference Paper IEEE 2019Deep Learning Based Container Text RecognitionPublished in: 2019 IEEE 23rd International Conference on Computer Supported Cooperative Work in Design (CSCWD)https://ieeexplore.ieee.org/document/8791876, Hand gestures are a powerful environment for communicating with communities with intellectual disability. To resolve this problem, smart and auto attendance management system is being utilized. Results proof the general effectiveness of the methodology and motivate the application to specific inspection tasks. The project is good to understand how to detect objects with different kinds of sh… Published in: 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP). In the decoding module, the skip layer connection is used to propagate context information to higher resolution layers, so as to prevent low-level information from passing the entire network structure. There are two kinds of methods that are currently popular in developed face recognition pattern namely, Eigenface method and Fisherface method. In the machine vision area, image recognition refers to the ability of software to identify people, objects, places, or actions in images. The localization effects of TBD, RGI, PAORGB, and ASPS methods were comparatively evaluated by IoU indicators, and the accuracy of benign and malignant diagnosis of those methods are evaluated by Accuracy, Sensitivity, Specificity, and AUC. In this paper, we describe an approach for real-time automatic detection of abandoned luggage in video captured by surveillance cameras. This project is a first step towards a smart hand gesture recognition set up for Collaborative Robots using a Faster R-CNN Object Detector to find the accurate position of the hands in RGB images. One of the most important application of Image processing is Facial expression recognition. Two extensions to the basic system are presented that mitigate the possibility of discovering the content of the hidden image. >>> images = list(zip(digits_data.images, digits_data.target)) The zip() function joins together the handwritten images and the target labels. Our method employs different deep learning models for accurate food identification. Developed by researchers from Columbia University, the University of Maryland, and the Smithsonian Institution, this series of free mobile apps uses visual recognition software to help users identify tree species from photos of their leaves. This proposed method fills the corrupted area by using similarity of the boundary pixels values around that corrupted regions in every iteration step. The similar threshold homogeneity pixel is grouped. Finally, video copy detection is efficiently and effectively implemented based on the extracted spatio-temporal CNN features. We first train a supervised convolutional neural network (CNN) to learn the hierarchical features of deblocking operations with labeled patches from the training datasets. Image-Classification-with-Transfer-Learning Project Summary. Gesture recognition continues to be a daunting task. If there is a single class, the term "recognition" is often applied, whereas a multi-class … In such a place, the environment must be made hassle-free. A deep network consisting of Regional convolutional neural network (CNN) and recurrent neural network is designed.The experimental results show that the proposed method not only locates license plates of different countries accurately but also be robust to scenes of illumination variation, noise distortion, and blurry effects. Our system can efficiently detect head and facial features. The implementation results have confirmed that bacteria images from microscope are able to recognize the genus of bacterium. According to the performance of AlexNet in classification, it was used to diagnose benign and malignant lesions. Thus, it encourages increasing of the productivity through the fast recognition of disease and the consequent action. The final segmented retina vessels contain more noise with low classification accuracy. In this paper we compare three architectures (YOLO, Faster R-CNN, SSD) by the following criteria: processing speed, mAP, precision and recall. The algorithm shows better detection rate and accuracy compared with Bayesian classifiers available in WEKA. The proposed algorithm consists of two networks. This paper improves the network structure of YOLO algorithm and proposes a new network structure YOLO-R. First, three Passthrough layers were added to the original YOLO network. Reference Paper IEEE 2019 Deep Learn Helmets-Enhancing Security at ATMs Published in: 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) https://ieeexplore.ieee.org/document/8728493, Your email address will not be published. Driver drowsiness detection is a key technology that can prevent fatal car accidents caused by drowsy driving. The Image can be of handwritten document or Printed document. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale transformers image-classification image-recognition vit vision … Second, we build a feature set fusing deep features, morphological features, texture features, and density features. Reference Paper IEEE 2019 Selection-based subpixel-shifted images super-resolution Published in: IEEE Access ( Early Access ) https://ieeexplore.ieee.org/document/8794494. In this study, the authors propose a modification of this algorithm, namely new enhanced EZW (NE-EZW), allowing to achieve a high compression performance in terms of peak-signal-to-noise ratio and bitrate for lossy image compression. Some popular applications of eye tracking through gaze estimation are depicted in Fig. Moving vehicles are then detected by analyzing the pixel wise variations between estimated background and input frames. Computerized security frameworks are fundamental at this point. Features used are the Y coordinates of joints and classifier used is K Nearest Neighbor. The system is trained on images drawn randomly from the ImageNet database, and works well on natural images from a wide variety of sources. There has been a rapid increase in dietary ailments during the last few decades, caused by unhealthy food routine. As an alternative, two-dimensional face recognition based on the built-in visible-light camera of mobile devices has been widely used. Face detection is the pre-step for face recognition that is performed using Haar-like features. Then, the estimation models for the robot position and the line landmark are derived as simple linear equations. Then, we produce a large set of “multi-class” artificial samples, by interchanging the periocular and ocular parts from different subjects. Afterward, the text regions of the enhanced image are detected by employing the Maximally Stable External Regions (MSER) feature detector. Our goal is to make them lead a life which is of security and safety for their own well being. Image recognition is an application of such tech future that changed the way we used to see the world. The proposed system consists of a camera which detects the commodity using Deep Learning techniques and a load cell which measures the weight of the commodity attached to the shopping cart. However, it triggers a decrease in productivity as no taking appropriate action and time. Face recognition is one of the biometric methods to improve this system. This paper presents the process of integrating digital watermarking technique into medical imaging workflow to evaluate, validate and verify its applicability and appropriateness to medical domains. Iris, fingerprint, and three-dimensional face recognition technologies used in mobile devices face obstacles owing to price and size restrictions by additional cameras, lighting, and sensors. Reference Paper IEEE 2019 BallTrack: Football ball tracking for real-time CCTV systems Published in: 2019 16th International Conference on Machine Vision Applications (MVA) https://ieeexplore.ieee.org/document/8757880. We use the combined dilated convolution to effectively enlarge the receptive field of the network and alleviate the “grid problem” that exists in the standard dilated convolution. The image analysis and detection has been very significant in various applications. Human unique finger impression is wealthy in detail called particulars, which can be utilized as recognizable proof imprints for unique fingerprint confirmation. ... (SFDL) method for image set based face recognition, where each training and testing example contains a set of face images which were captured from different variations of pose, illumination, expression, resolution and motion. The analysis result is immediately sent to the farmer required the decision and then feedback from the farmer is reflected to the model. In contrast, deep convolutional neural networks (CNN) are able to perform both the feature extraction and classification tasks simultaneously by internal hierarchical learning. For this reason, in this paper, we introduce computation optimizations of the implemented algorithm to keep the integer part of arithmetic operations at optimal size, and, hence, arithmetic units as small as possible. Three different hardware-architecture variants, two for image watermarking and one for video (pipelined), are proposed, which reutilize the already small arithmetic units in different computation steps, to further reduce implementation cost. Finally, extensive experimental results show that their denoiser is effective for those images with a large number of interference pixels which may cause misjudgement. Visual Search for Improved Product Discoverability. In this way, the bag-of-encrypted-words (BOEW) model is built to represent each image by a feature vector, i.e., a normalized histogram of the encrypted visual words. During the last few years, we've seen quite a few apps powered by image recognition technologies appear on the market. How It Works. Reference Paper IEEE 2019Semantic Food Segmentation for Automatic Dietary MonitoringPublished in: 2018 IEEE 8th International Conference on Consumer Electronics – Berlin (ICCE-Berlin)https://ieeexplore.ieee.org/document/8576231. The proposed system prototype is realized. The list() method creates a list of the concatenated images and labels. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. Check out the knowledge base collected and distilled by experienced professionals. As a major novelty, we describe a processing chain based on convolution neural networks (CNNs) that defines the regions-of-interest in the input data that should be privileged in an implicit way, i.e., without masking out any areas in the learning/test samples. The non-text MSERs are removed by employing appropriate filters. Reference Paper IEEE 2019Glaucoma Detection Using Fundus Images of The EyePublished in: 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA)https://ieeexplore.ieee.org/document/8730250. Face recognition is achieved using Deep Learning’s sub-field that is Convolutional Neural Network (CNN). In this work, the ripeness of the banana is classified into three different class of maturity; unripe, ripe and overripe systematically based on their key attributes value.