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Face Recognition (FR) is considered as a heavily studied topic in computer vision field. The capability to automatically identify and authenticate human’s faces using real-time images is an important aspect in surveillance, security, and other related domains. There are separate applications that help in identifying individuals at specific locations which help in detecting intruders. The…

Online fashion market is constantly growing, and an algorithm capable of identifying garments can help companies in the clothing sales sector to understand the profile of potential buyers and focus on sales targeting specific niches, as well as developing campaigns based on the taste of customers and improve user experience. Artificial Intelligence approaches able to…

Feature extraction is an important process in image classification for achieving an efficient accuracy for the classification learning models. One of these methods is using the convolution neural networks. The use of the trained classic deep convolution neural networks as features extraction gives a considerable results in the remote sensing images classification models. So, this…

As models based in artificial intelligence increase in sophistication, there is a higher demand for the integration of hardware components to heighten real-world implementations. Both facial feature tracking and shape-from-focus are known techniques in computer vision. However, the combination of these two elements, particularly in a cost-effective configuration, has not been extensively explored. In this…

Providing timely and meaningful feedback in photography education is challenging, particularly in large classes where manual assessment can delay skill development. This paper presents M-Stock, an AI-based automated photo evaluation system that uses Convolutional Neural Networks (CNNs) to assess student photography assignments on web browser. M-Stock evaluates both technical aspects (such as lighting, composition, and…

Aging is considered to be a complex process in almost every species’ life, which can be studied at a variety of levels of abstraction as well as in different organs. Not surprisingly, biometric characteristics from facial images play a significant role in predicting human’s age. Specifically, automatic age estimation in real-time situation has begun to…

DNN implementation and deployment is quite a challenge within a resource constrained environment on real-time embedded platforms. To attain the goal of DNN tailor made architecture deployment on a real-time embedded platform with limited hardware resources (low computational and memory resources) in comparison to a CPU or GPU based system, High Performance SqueezeNext (HPS) architecture…

An automatic speech recognition (ASR) is a key technology for preventing an ongoing global coronavirus epidemic. Due to the limited corpus database and the morphological diversity of the Thai language, Thai speech recognition is still difficult. In this research, the automatic speech recognition model was built differently from the traditional Thai NLP systems by using…

Depth prediction plays a key role in understanding a 3D scene. Several techniques have been developed throughout the years, among which Convolutional Neural Network has recently achieved state-of-the-art performance on estimating depth from a single image. However, traditional CNNs suffer from the lower resolution and information loss caused by the pooling layers. And oversized parameters…

To evaluate and compare methods in computer vision, scientists must use a benchmark dataset and unified sets of measurements. The UCI-EGO dataset is a standard benchmark dataset for evaluating Hand Pose Estimation (HPE) on depth images. To build robotic arms that perform complex operations such as human hands, the poses of the human hand need…

ECG analysis is commonly used by medical practitioners and cardiologists for monitoring cardiac health. A high-performance automatic ECG classification system is a challenging area because there is difficulty in detecting and clustering various waveforms in the signal, especially in the manual analysis of electrocardiogram (ECG) signals. In this paper, an accurate (ECG) classification and monitoring…

Suppose we want to classify a query item Q with a classification model that consists of a large set of predefined classes L and suppose we have a knowledge that indicates to us that the target class of Q belongs to a small subset from L. Naturally, this filtering will improve the accuracy of any…

Restoring, estimating the fully 3D hand skeleton and pose from the image data of the captured sensors/cameras applied in many applications of computer vision and robotics: human-computer interaction; gesture recognition, interactive games, Computer-Aided Design (CAD), sign languages, action recognition, etc. These are applications that flourish in Virtual Reality and Augmented Reality (VR/AR) technologies. Previous survey…

Convolutional Neural Networks (CNNs) have gained attention in recent years for their ability to perform complex machine learning tasks with high accuracy and resilient to noise of inputs. The time-consuming convolution operations of CNNs pose great challenges to both software as well as hardware designers. To achieve superior performance, a design involves careful concerns between…