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Pixeltests an EdTech Impacted over 110,000 Professionals in Cutting Edge Technology

Bengaluru (Karnataka) [India], September 5 (ANI/NewsVoir): Pixeltests is an education technology (EdTech) startup that is well on its way in its mission to upskill over a million professionals and students in the emergent and game-changing technologies of Web 3.0 and Artificial Intelligence (AI). Pixeltests' work will help them secure fulfilling and lucrative opportunities in these industry-relevant technologies. To that end, Pixeltests has partnerships in place with IIT-Madras Center for Co...
United States Naveen Vunnam Raghu Gullapalli Arunv Rao Jayanth Rasamsetti Ganesh Vudutha

"Efficient hyperspectral image segmentation for biosecurity scanning us" by Minh Hieu Phan, Son Lam Phung et al.

Foreign species can deteriorate the environment and the economy of a country. To automatically monitor biosecurity threats at country borders, this paper investigates compact deep networks for accurate and real-time object segmentation for hyperspectral images. To this end, knowledge distillation (KD) approaches compress the model by distilling the knowledge of a large teacher network to a compact student network. However, when the student is over-compressed, the performance of standard KD metho...
Knowledge Distillation Multi Head Teacher Deep Learning Yperspectral Image Segmentation Knowledge Distillation
Source: uow.edu.au

"Industrial IoT intrusion detection via evolutionary cost-sensitive lea" by Akbar Telikani, Jun Shen et al.

Cyber-attacks and intrusions have become the major obstacles to the adoption of the Industrial Internet of Things (IIoT) in critical industries. Imbalanced data distribution is a common problem in IIoT environments that negatively influence machine learning-based intrusion detection systems. To address this issue, we introduce EvolCostDeep, a hybrid model of stacked auto-encoders (SAE) and convolutional neural networks (CNNs) with a new cost-dependent loss function. The loss function aims to opt...
Industrial Internet Class Imbalance Computational Modeling Convolutional Neural Networks Cost Sensitive Learning Deep Learning
Source: uow.edu.au

"TreeNet Based Fast Task Decomposition for Resource-Constrained Edge In" by Dong Lu, Yanlong Zhai et al.

Edge intelligence is an emerging technology that integrates edge computing and deep learning to bring AI to the network’s edge. It has gained wide attention for its lower network latency and better privacy preservation abilities. However, the inference of deep neural networks is computationally demanding and results in poor real-time performance, making it challenging for resource-constrained edge devices. In this paper, we propose a hierarchical deep learning model based on TreeNet to reduce ...
Adaptation Models Computational Modeling Deep Learning Edge Computing Edge Intelligence Odel Acceleration
Source: uow.edu.au

"Prediction of hydraulic blockage at culverts from a single image using" by Umair Iqbal, Johan Barthelemy et al.

Cross-drainage hydraulic structures such as culverts and bridges in urban landscapes are prone to get blocked by the transported debris (e.g., urban, vegetated), which often reduces their hydraulic capacity and triggers flash floods. Unavailability of relevant data from blockage-originated flooding events and complex nature of debris accumulation are highlighted factors hindering the research within the blockage management domain. Wollongong City Council (WCC) blockage conduit policy is the lead...
Lab Dataset Wollongong City Council Lab Blockage Dataset City Council Artificial Intelligence Hydraulics Lab Blockage Dataset
Source: uow.edu.au

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AWS on democratizing machine learning for everyone

Artificial Intelligence (AI) and Machine Learning (ML) are two buzzwords that became quite popular during this ongoing pandemic. Nowadays, it is rather common for us to hear businesses and organizations talk about their adoption of AI and ML in their respective fields. What really are AI and ML, and
Donnie Prakoso Ai Services Amazon Web Services Aml Services Artificial Intelligence Machine Learning
Source: mb.com.ph

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