Hybrid quantum-classical convolutional neural network model for image classification
Image classification plays an important role in remote sensing. Earth observation (EO) has
inevitably arrived in the big data era, but the high requirement on computation power has …
inevitably arrived in the big data era, but the high requirement on computation power has …
Weakly supervised video anomaly detection via transformer-enabled temporal relation learning
Weakly supervised video anomaly detection is a challenging problem due to the lack of
frame-level labels in training videos. Most previous works typically tackle this task with the …
frame-level labels in training videos. Most previous works typically tackle this task with the …
Fuzzy wavelet neural network driven vehicle detection on remote sensing imagery
Remote sensing-based target detection process is applied to spot the targeted objects in
remote sensing images (RSIs). However, it is challenging to detect small-sized vehicles in …
remote sensing images (RSIs). However, it is challenging to detect small-sized vehicles in …
An evaluation of hardware-efficient quantum neural networks for image data classification
Quantum computing is expected to fundamentally change computer systems in the future.
Recently, a new research topic of quantum computing is the hybrid quantum–classical …
Recently, a new research topic of quantum computing is the hybrid quantum–classical …
Hybrid quantum neural network structures for image multi-classification
M Shi, H Situ, C Zhang - Physica Scripta, 2024 - iopscience.iop.org
Image classification is a fundamental problem in computer vision, and neural networks
provide an effective solution. With the advancement of quantum technology, quantum neural …
provide an effective solution. With the advancement of quantum technology, quantum neural …
Mixed-species cover crop biomass estimation using planet imagery
Cover crop biomass is helpful for weed and pest control, soil erosion control, nutrient
recycling, and overall soil health and crop productivity improvement. These benefits may …
recycling, and overall soil health and crop productivity improvement. These benefits may …
Optimal Fuzzy Deep Neural Networks based Plant Disease Detection and Classification on UAV-based Remote Sensed Data
Unmanned Aerial Vehicles (UAVs) equipped with remote sensing (RS) abilities have
revolutionized agriculture practices, especially in the area of plant disease detection, with …
revolutionized agriculture practices, especially in the area of plant disease detection, with …
Land Cover Classification From Sentinel-2 Images With Quantum-Classical Convolutional Neural Networks
Exploiting machine learning techniques to automatically classify multispectral remote
sensing imagery plays a significant role in deriving changes on the Earth's surface …
sensing imagery plays a significant role in deriving changes on the Earth's surface …
EQID: Entangled quantum image descriptor an approach for early plant disease detection
In present day agriculture, early and accurate identification of plant diseases is essential for
prompt response, which protects crop quality and output. This paper presents the Entangled …
prompt response, which protects crop quality and output. This paper presents the Entangled …
Intracranial hemorrhage subtype classification using learned fully connected separable convolutional network
In recent decades, intracranial hemorrhage detection from computed tomography (CT)
scans has gained considerable attention among researchers in the medical community. The …
scans has gained considerable attention among researchers in the medical community. The …