In this paper, we address the question of achieving high accuracy in deep learning models
for agricultural applications through edge computing devices while considering the …

Object detection is a widely applied approach in addressing many real-world computer
vision challenges. Despite its importance, object detection is computationally intensive and …

Deep neural network (DNN) inference service at the edge is promising, but it is still non-
trivial to achieve high-throughput for multi-DNN model deployment on resource-constrained …

Coastal wetlands and nearshore environments significantly contribute to carbon storage,
accounting for nearly half of global blue carbon. However, threats like climate change …

Artificial intelligence workloads, especially transformer models, exhibit emergent sparsity in
which computations perform selective sparse access to dense data. The workloads are …

Several Virtual Machines (VMs) belonging to various users transparently share physical
resources in multi-tenancy cloud milieu. In these situations, implementing an effective …

The unprecedented success of Deep Learning (DL) algorithms, or Deep Neural Networks
(DNNs), is driving the trend toward deploying them in a variety of environments including …