Multimodal contrastive learning for face anti-spoofing
Multimodal face anti-spoofing systems adopt multiple sensor modalities, such as infrared,
color, depth, and thermal, to distinguish between living and spoofing faces via …
color, depth, and thermal, to distinguish between living and spoofing faces via …
[HTML][HTML] Object segmentation for image indexing in large database
It is a challenging task to devise an effective model for object segmentation considering
numerous classes because different classes might have different features and different …
numerous classes because different classes might have different features and different …
[HTML][HTML] Collaborative gas source localization strategy with networked nano-drones in unknown cluttered environments
This paper introduces a novel approach for improving gas source localization in dynamic
urban environments, employing a swarm of nano-Crazyflie drones through a hybrid strategy …
urban environments, employing a swarm of nano-Crazyflie drones through a hybrid strategy …
[HTML][HTML] Automatic melanoma detection using discrete cosine transform features and metadata on dermoscopic images
Abstract Machine learning contributes in improving the accuracy of melanoma detection.
There are extensive studies in classic and deep learning-based approaches for melanoma …
There are extensive studies in classic and deep learning-based approaches for melanoma …
HARWE: A multi-modal large-scale dataset for context-aware human activity recognition in smart working environments
A Esmaeilzehi, E Khazaei, K Wang, NK Kalsi… - Pattern Recognition …, 2024 - Elsevier
In recent years, deep neural networks (DNNs) have provided high performances for various
tasks, such as human activity recognition (HAR), in view of their end-to-end training process …
tasks, such as human activity recognition (HAR), in view of their end-to-end training process …
Lip-Reading Advancements: A 3D Convolutional Neural Network/Long Short-Term Memory Fusion for Precise Word Recognition
Lip reading, the art of deciphering spoken words from the visual cues of lip movements, has
garnered significant interest for its potential applications in diverse fields, including assistive …
garnered significant interest for its potential applications in diverse fields, including assistive …
Learning discriminative context for salient object detection
G Zhu, L Wang, J Tang - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Context understanding is important for salient object detection (SOD) in complex scenes. To
alleviate visual confusion, we propose a context aware network that full use of the same type …
alleviate visual confusion, we propose a context aware network that full use of the same type …
A hybrid human recognition framework using machine learning and deep neural networks
AM Sheneamer, MH Halawi, MH Al-Qahtani - PLOS ONE, 2024 - journals.plos.org
Faces are a crucial environmental trigger. They communicate information about several key
features, including identity. However, the 2019 coronavirus pandemic (COVID-19) …
features, including identity. However, the 2019 coronavirus pandemic (COVID-19) …
A hybrid deep learning framework for daily living human activity recognition with cluster-based video summarization
In assisted living facilities or nursing homes, residents' movements or actions can be
monitored using Human Activity Recognition (HAR), ensuring they receive proper care and …
monitored using Human Activity Recognition (HAR), ensuring they receive proper care and …
FSErasing: Improving Face Recognition with Data Augmentation Using Face Parsing
H Kawai, K Ito, HT Chen, T Aoki - IET Biometrics, 2024 - Wiley Online Library
We propose original semantic labels for detailed face parsing to improve the accuracy of
face recognition by focusing on parts in a face. The part labels used in conventional face …
face recognition by focusing on parts in a face. The part labels used in conventional face …