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View article: Statistical Approaches to Evaluating Artificial Intelligence Models in Healthcare
Statistical Approaches to Evaluating Artificial Intelligence Models in Healthcare Open
This study reviews statistical frameworks utilized in an evaluation of artificial intelligence (AI) modeling ability to identify death in heart failure patients. Descriptive statistics, and correlation analyses had been employed to describ…
View article: ConVLM: Context-guided vision-language model for fine-grained histopathology image classification
ConVLM: Context-guided vision-language model for fine-grained histopathology image classification Open
View article: Visual tracking by matching points using diffusion model
Visual tracking by matching points using diffusion model Open
View article: CLDTracker: A Comprehensive Language Description for visual Tracking
CLDTracker: A Comprehensive Language Description for visual Tracking Open
View article: MVTD: A Benchmark Dataset for Maritime Visual Object Tracking
MVTD: A Benchmark Dataset for Maritime Visual Object Tracking Open
Visual Object Tracking (VOT) is a fundamental task with widespread applications in autonomous navigation, surveillance, and maritime robotics. Despite significant advances in generic object tracking, maritime environments continue to prese…
View article: CLDTracker: A Comprehensive Language Description for Visual Tracking
CLDTracker: A Comprehensive Language Description for Visual Tracking Open
VOT remains a fundamental yet challenging task in computer vision due to dynamic appearance changes, occlusions, and background clutter. Traditional trackers, relying primarily on visual cues, often struggle in such complex scenarios. Rece…
View article: snnTrans-DHZ: A Lightweight Spiking Neural Network Architecture for Underwater Image Dehazing
snnTrans-DHZ: A Lightweight Spiking Neural Network Architecture for Underwater Image Dehazing Open
Underwater image dehazing is critical for vision-based marine operations because light scattering and absorption can severely reduce visibility. This paper introduces snnTrans-DHZ, a lightweight Spiking Neural Network (SNN) specifically de…
View article: Underwater Image Enhancement by Convolutional Spiking Neural Networks
Underwater Image Enhancement by Convolutional Spiking Neural Networks Open
Underwater image enhancement (UIE) is fundamental for marine applications, including autonomous vision-based navigation. Deep learning methods using convolutional neural networks (CNN) and vision transformers advanced UIE performance. Rece…
View article: Learning Spatial–Temporal Regularized Tensor Sparse RPCA for Background Subtraction
Learning Spatial–Temporal Regularized Tensor Sparse RPCA for Background Subtraction Open
Background subtraction in videos is a core challenge in computer vision, aiming to accurately identify moving objects. Robust principal component analysis (RPCA) has emerged as a promising unsupervised (US) paradigm for this task, showing …
View article: Author Correction: Drone-Person Tracking in Uniform Appearance Crowd: A New Dataset
Author Correction: Drone-Person Tracking in Uniform Appearance Crowd: A New Dataset Open
View article: EfficientFaceV2S: A lightweight model and a benchmarking approach for drone-captured face recognition
EfficientFaceV2S: A lightweight model and a benchmarking approach for drone-captured face recognition Open
View article: AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis
AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis Open
The preservation of aquatic biodiversity is critical in mitigating the effects of climate change. Aquatic scene understanding plays a pivotal role in aiding marine scientists in their decision-making processes. In this paper, we introduce …
View article: Anomaly Detection for Industrial Applications, Its Challenges, Solutions, and Future Directions: A Review
Anomaly Detection for Industrial Applications, Its Challenges, Solutions, and Future Directions: A Review Open
Anomaly detection from images captured using camera sensors is one of the mainstream applications at the industrial level. Particularly, it maintains the quality and optimizes the efficiency in production processes across diverse industria…
View article: Robust Face Detection and Identification under Occlusion using MTCNN and RESNET50
Robust Face Detection and Identification under Occlusion using MTCNN and RESNET50 Open
In today's rapidly evolving world, where technology is progressing swiftly, there is an increasing demand for facial recognition systems. Technologies are similar to digital forensics in that they can recognize people by scanning faces. Ho…
View article: Few-Shot Segmentation Using Multi-Similarity and Attention Guidance
Few-Shot Segmentation Using Multi-Similarity and Attention Guidance Open
Few-shot segmentation (FSS) methods aim to segment objects of novel classes with relatively few annotated samples. Prototype learning, a popular approach in FSS, employs prototype vectors to transfer information from known classes (support…
View article: Optimized Flare Performance Analysis Through Multi-Modal Machine Learning and Temporal Standard Deviation Enhancements
Optimized Flare Performance Analysis Through Multi-Modal Machine Learning and Temporal Standard Deviation Enhancements Open
Flaring is a routine practice in the upstream gas industry to dispose of waste gases, but its efficiency can drop significantly under non-ideal conditions such as crosswinds, over-aeration, or over-steaming. These inefficiencies lead to in…
View article: ELTrack: Events-Language Description for Visual Object Tracking
ELTrack: Events-Language Description for Visual Object Tracking Open
The integration of Natural Language (NL) descriptions into Visual Object Tracking (VOT) has shown promise in enhancing the performance of RGB-based tracking by providing richer, contextually aware information that helps to address issues l…
View article: Training-Free VLM-Based Pseudo Label Generation for Video Anomaly Detection
Training-Free VLM-Based Pseudo Label Generation for Video Anomaly Detection Open
Video anomaly detection in weakly supervised settings remains a challenging task due to the absence of frame-level annotations. To address this, we propose a novel training-free pseudo-label generation module (TFPLG) for Weakly Supervised …
View article: AITtrack: Attention-Based Image-Text Alignment for Visual Tracking
AITtrack: Attention-Based Image-Text Alignment for Visual Tracking Open
Vision-Language Models (VLMs) have recently advanced the Visual Object Tracking (VOT) performance. In VLMs, a vision encoder is employed to obtain visual representation, and a text encoder is employed to estimate the textual embeddings usi…
View article: A SEMANTIC FAKE NEWS DETECTION SYSTEM USING MACHINE LEARNING CLASSIFIER
A SEMANTIC FAKE NEWS DETECTION SYSTEM USING MACHINE LEARNING CLASSIFIER Open
The purpose of fake news detection system is to build ontology to find hypothesis involved in misleading social media users through automated reasoning. Ontology for classification of news content has been created after understanding the s…
View article: Neuromorphic Vision-Based Motion Segmentation With Graph Transformer Neural Network
Neuromorphic Vision-Based Motion Segmentation With Graph Transformer Neural Network Open
View article: Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain
Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain Open
This paper delves into the potential of DU-VIO, a dehazing-aided hybrid multi-rate multi-modal Visual-Inertial Odometry (VIO) estimation framework, designed to thrive in the challenging realm of extreme underwater environments. The cutting…
View article: Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework
Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Open
This paper introduces the concept of employing neuromorphic methodologies for task-oriented underwater robotics applications. In contrast to the increasing computational demands of conventional deep learning algorithms, neuromorphic techno…
View article: Advancing Histopathology with Deep Learning Under Data Scarcity: A Decade in Review
Advancing Histopathology with Deep Learning Under Data Scarcity: A Decade in Review Open
Recent years witnessed remarkable progress in computational histopathology, largely fueled by deep learning. This brought the clinical adoption of deep learning-based tools within reach, promising significant benefits to healthcare, offeri…
View article: Predicting the Best of N Visual Trackers
Predicting the Best of N Visual Trackers Open
We observe that the performance of SOTA visual trackers surprisingly strongly varies across different video attributes and datasets. No single tracker remains the best performer across all tracking attributes and datasets. To bridge this g…
View article: CPLIP: Zero-Shot Learning for Histopathology with Comprehensive Vision-Language Alignment
CPLIP: Zero-Shot Learning for Histopathology with Comprehensive Vision-Language Alignment Open
This paper proposes Comprehensive Pathology Language Image Pre-training (CPLIP), a new unsupervised technique designed to enhance the alignment of images and text in histopathology for tasks such as classification and segmentation. This me…
View article: Video Anomaly Detection in 10 Years: A Survey and Outlook
Video Anomaly Detection in 10 Years: A Survey and Outlook Open
Video anomaly detection (VAD) holds immense importance across diverse domains such as surveillance, healthcare, and environmental monitoring. While numerous surveys focus on conventional VAD methods, they often lack depth in exploring spec…
View article: Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Network
Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Network Open
Moving object segmentation is critical to interpret scene dynamics for robotic navigation systems in challenging environments. Neuromorphic vision sensors are tailored for motion perception due to their asynchronous nature, high temporal r…
View article: Unsupervised Dual Transformer Learning for 3-D Textured Surface Segmentation
Unsupervised Dual Transformer Learning for 3-D Textured Surface Segmentation Open
Analysis of the 3-D texture is indispensable for various tasks, such as retrieval, segmentation, classification, and inspection of sculptures, knit fabrics, and biological tissues. A 3-D texture represents a locally repeated surface variat…
View article: Accurate and Efficient Urban Street Tree Inventory with Deep Learning on Mobile Phone Imagery
Accurate and Efficient Urban Street Tree Inventory with Deep Learning on Mobile Phone Imagery Open
Deforestation, a major contributor to climate change, poses detrimental consequences such as agricultural sector disruption, global warming, flash floods, and landslides. Conventional approaches to urban street tree inventory suffer from i…