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Deep Learning Methods for Precise Sugarcane Disease Detection and Sustainable Crop Management
In the agricultural domain, sugarcane crops, like many others, are susceptible to diseases, posing a significant threat to both quality and quantity...
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A Tale of Two Boards: On the Influence of Microarchitecture on Side-Channel Leakage
Advances in cryptography have enabled the features of confidentiality, security, and integrity on small embedded devices such as IoT devices. While...
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Consistency Guided Multiview Hypergraph Embedding Learning with Multiatlas-Based Functional Connectivity Networks Using Resting-State fMRI
Recently, resting-state functional connectivity network (FCN) analysis via graph convolutional networks (GCNs) has greatly boosted diagnostic...
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Smart Saliency Detection for Prosthetic Vision
People with visual impairments often have difficulty locating misplaced objects. This can be a major barrier to their independence and quality of...
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Probabilistic object tracking by low power microcontrollers
Low power microcontrollers have become widely available. Hence, they have been used in several stand-alone applications in which the developed system...
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Class-Aware Feature Alignment for Domain Adaptative Mitochondria Segmentation
Unsupervised domain adaptation (UDA) has gained great popularity in mitochondria segmentation, aiming to improve the adaptability of models from the...
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A Methodology for Evaluating the Energy Efficiency of Post-Moore Architectures
The improvement of computational systems has been based on Moore’s law and Dennard’s scale, but for more than a decade it has started to fall to a...
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Using Co-word Network Community Detection and LDA Topic Modeling to Extract Topics in TED Talks
Two topic detection techniques—co-word network analysis and topic modeling—were applied to extract topics in the Ted Talks. Ted Talks was chosen for...
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Energy data classification at the edge: a comparative study for energy efficiency applications
As the global economy is increasingly influenced by energy policy and efficiency, the opportunities of energy data classification are broadening....
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Fostering inclusivity through effective communication: Real-time sign language to speech conversion system for the deaf and hard-of-hearing community
In a world that values inclusivity, effective communication remains a cornerstone of empowerment for the deaf and hard-of-hearing community, with...
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An Empirical Study on the Robustness of Active Learning for Biomedical Image Classification Under Model Transfer Scenarios
Active learning (AL) is a popular training strategy that involves iteratively selecting training examples for annotation, typically those for which...
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Joint Estimation of Neural Events and Hemodynamic Response Functions from Task fMRI via Convolutional Neural Networks
Joint decomposition of functional magnetic resonance imaging (fMRI) time series into time courses of neural activity events and hemodynamic response...
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Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models
Interpretability is a critical factor in applying complex deep learning models to advance the understanding of brain disorders in neuroimaging...
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Maximum Subgraph Problem for 3-Regular Knödel graphs and its Wirelength
The maximum subgraph problem (MSP) of a graph is the estimation of the greatest number of edges in the induced subgraph of all subsets of the vertex...
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An Adaboost Support Vector Machine Based Harris Hawks Optimization Algorithm for Intelligent Quotient Estimation from MRI Images
Human intelligence is measured using the Intelligent Quotient (IQ) score which is derived from a range of tests. Due to a lack of a large dataset, IQ...
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Perception of Cyber Threats
This chapter presents an approach to improve cyber threat perception using Autonomous Intelligent Cyber-defence Agents (AICA). Recent research has...
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SBIR-BYOL: a self-supervised sketch-based image retrieval model
Sketch-based image retrieval is demanding interest in the computer vision community due to its relevance in the visual perception system and its...
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Pre-trained Deep Networks for Faster Region-Based CNN Model for Pituitary Tumor Detection
Due to drastic changes in the field of technology and computing power for the last decade, it has become very easy to implement the convolutional...
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Fundamental Considerations on Representation Learning for Multimodal Processing
In recent years, there has been an extremely active research boom in the fields of machine learning, particularly in artificial neural networks...