Academic Articles & Research Papers

Data Efficient Vision Transformer Based Model for Brain Tumor Classification in MRI

Accurate detection of brain tumors at early stages is crucial for clinical diagnosis and treatment planning. Magnetic Resonance Imaging (MRI) is the most popular method due to its soft-tissue contrast and spatial resolution. However, manual...

Artificial Intelligence in Healthcare: Advancing Innovation and Ethics to Foster Well-Being

Artificial intelligence (AI) is reshaping healthcare by enhancing diagnostic precision, treatment personalization, and overall patient care. By leveraging technologies such as machine learning, deep learning, natural language processing, an...

A Survey of Computer Vision-Based Human Motion Capture

Computer Vision: A First Course

Computer vision is a new discipline recently developed from image processing, which is able to take raw images, and, after suitable processing, derive information from them automatically. Computer vision applications are legion in the areas...

Template Matching Techniques in Computer Vision

The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling huma...

Attention is All Large Language Model Need

With the advent of the Transformer, the attention mechanism has been applied to Large Language Model (LLM), evolving from initial single- modal large models to today's multi-modal large models. This has greatly propelled the development of ...

Object detection in crowded scenes via joint prediction

Detecting highly-overlapped objects in crowded scenes remains a challenging problem, especially for one-stage detector. In this paper, we extricate YOLOv4 from the dilemma in a crowd by fine-tuning its detection scheme, named YOLO-CS. Speci...

Computer Vision Analysis of Intraoperative Video

OBJECTIVE(S): To develop and assess AI algorithms to identify operative steps in laparoscopic sleeve gastrectomy (LSG). BACKGROUND: Computer vision, a form of artificial intelligence (AI), allows for quantitative analysis of video by comput...

Exploiting Three-Dimensional Gaze Tracking for Action Recognition During Bimanual Manipulation to Enhance Human–Robot Collaboration

Human–robot collaboration could be advanced by facilitating the intuitive, gaze-based control of robots, and enabling robots to recognize human actions, infer human intent, and plan actions that support human goals. Traditionally, gaze trac...

A Comparative Study of Physically Accurate Synthetic Shadow Datasets in Agricultural Settings with Human Activity

Shadow, a natural phenomenon resulting from the absence of light, plays a pivotal role in agriculture, particularly in processes such as photosynthesis in plants. Despite the availability of generic shadow datasets, many suffer from annotat...

IEEE Workshop on Applications of Computer Vision

The following topics are discussed: computer vision; image processing; face recognition; robotics; navigation; visual surveillance; indexing; image restoration; human-computer interaction; and medical imaging...

Computer vision in the interface

There are still obstacles to achieving general, robust, high-performance computer vision systems. The last decade, however, has seen significant progress in vision technologies for human-computer interaction....

Attention mechanisms in computer vision: A survey

Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an ...

Multi-scale attention and collaborative fusion for enhanced RGB-D salient object detection in weld quality inspection

Abstract Salient object detection (SOD) plays a crucial role in computer vision by mimicking human visual attention to identify and segment the most prominent objects in a scene. The advent of depth sensing technologies has propelled RGB-D ...

Resource-Aware Scene Text Recognition Using Learned Features, Quantization, and Contour-Based Character Extraction

Scene texts serve as valuable information for humans and autonomous systems to make informed decisions. Processing scene texts poses significant difficulties for computer systems due to several factors, primarily due to variations in image ...

Crowdsourcing in Computer Vision

Computer vision systems require large amounts of manually annotated data to properly learn challenging visual concepts. Crowdsourcing platforms offer an inexpensive method to capture human knowledge and understanding, for a vast number of v...

Compatibility Effects With Simple Lever Tools: A Replication and Extension Beyond Simple Button Responses.

AI and Chatbot-Supported Interventions for Physical Activity and Obesity-Related Lifestyle Behaviors: Scoping Review With Attention to Family Involvement

Abstract BackgroundAI-enabled chatbots and related conversational systems can facilitate human–computer interaction through natural language, personalization, and automated support. In pediatric health promotion, these tools hav...

Evaluation of Similarity of Image Explanations Produced by SHAP, LIME and Grad-CAM

Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. They have achieved great success both in research and in practical applications in recent years, however, on...

Computer vision technology in agricultural automation —A review

Computer vision is a field that involves making a machine “see”. This technology uses a camera and computer instead of the human eye to identify, track and measure targets for further image processing. With the development of computer visio...