Critical insights into modern hyperspectral image applications through deep learning
Hyperspectral imaging has shown tremendous growth over the past three decades.
Hyperspectral imaging was evolved through remote sensing. Along, with the technological …
Hyperspectral imaging was evolved through remote sensing. Along, with the technological …
A deep learning model for classifying human facial expressions from infrared thermal images
The analysis of human facial expressions from the thermal images captured by the Infrared
Thermal Imaging (IRTI) cameras has recently gained importance compared to images …
Thermal Imaging (IRTI) cameras has recently gained importance compared to images …
Common sense knowledge infusion for visual understanding and reasoning: Approaches, challenges, and applications
Visual understanding involves detecting objects in a scene and investigating rich semantic
relationships between the objects, which is required for downstream visual reasoning tasks …
relationships between the objects, which is required for downstream visual reasoning tasks …
Hyperspectral imaging and deep learning for quantification of Clostridium sporogenes spores in food products using 1D-convolutional neural networks and random …
A Soni, M Al-Sarayreh, MM Reis, G Brightwell - Food Research International, 2021 - Elsevier
Clostridium sporogenes spores are used as surrogates for Clostridium botulinum, to verify
thermal exposure and lethality in sterilization regimes by food industries. Conventional …
thermal exposure and lethality in sterilization regimes by food industries. Conventional …
An intelligent fruits classification in precision agriculture using bilinear pooling convolutional neural networks
AJ Prakash, P Prakasam - The Visual Computer, 2023 - Springer
With an increase in the consumption of fruits day by day, the yielding and production around
the world are also increasing at a steady rate. Meanwhile, the workforce in the field becomes …
the world are also increasing at a steady rate. Meanwhile, the workforce in the field becomes …
Neuro-symbolic forward reasoning
Reasoning is an essential part of human intelligence and thus has been a long-standing
goal in artificial intelligence research. With the recent success of deep learning …
goal in artificial intelligence research. With the recent success of deep learning …
Multimodal event processing: A neural-symbolic paradigm for the internet of multimedia things
With the Internet of Multimedia Things (IoMT) becoming a reality, new approaches are
needed to process real-time multimodal event streams. Existing approaches to event …
needed to process real-time multimodal event streams. Existing approaches to event …
Expressive scene graph generation using commonsense knowledge infusion for visual understanding and reasoning
Scene graph generation aims to capture the semantic elements in images by modelling
objects and their relationships in a structured manner, which are essential for visual …
objects and their relationships in a structured manner, which are essential for visual …
Automatic image caption generation using deep learning
Image captioning is an interesting and challenging task with applications in diverse domains
such as image retrieval, organizing and locating images of users' interest, etc. It has huge …
such as image retrieval, organizing and locating images of users' interest, etc. It has huge …
NeuSyRE: Neuro-symbolic visual understanding and reasoning framework based on scene graph enrichment
Exploring the potential of neuro-symbolic hybrid approaches offers promising avenues for
seamless high-level understanding and reasoning about visual scenes. Scene Graph …
seamless high-level understanding and reasoning about visual scenes. Scene Graph …