[HTML][HTML] Insect classification and detection in field crops using modern machine learning techniques
T Kasinathan, D Singaraju, SR Uyyala - Information Processing in …, 2021 - Elsevier
The agriculture sector has an immense potential to improve the requirement of food and
supplies healthy and nutritious food. Crop insect detection is a challenging task for farmers …
supplies healthy and nutritious food. Crop insect detection is a challenging task for farmers …
Accurate iris segmentation and recognition using an end-to-end unified framework based on MADNet and DSANet
Y Chen, H Gan, H Chen, Y Zeng, L Xu, AA Heidari… - Neurocomputing, 2023 - Elsevier
Due to their insufficient generalization ability, iris segmentation algorithms based on deep
learning cannot accurately segment iris images without corresponding ground truth (GT) …
learning cannot accurately segment iris images without corresponding ground truth (GT) …
Iris recognition development techniques: a comprehensive review
JR Malgheet, NB Manshor, LS Affendey - Complexity, 2021 - Wiley Online Library
Recently, iris recognition techniques have achieved great performance in identification.
Among authentication techniques, iris recognition systems have received attention very …
Among authentication techniques, iris recognition systems have received attention very …
Multibiometric fusion strategy and its applications: A review
The unimodal biometric based system faced several inherent problems like lack of
uniqueness, intra-class variation, non-universality, noisy data (presence of dirt on the …
uniqueness, intra-class variation, non-universality, noisy data (presence of dirt on the …
An end to end deep neural network for iris segmentation in unconstrained scenarios
With the increasing imaging and processing capabilities of today's mobile devices, user
authentication using iris biometrics has become feasible. However, as the acquisition …
authentication using iris biometrics has become feasible. However, as the acquisition …
Deep learning-based iris segmentation for iris recognition in visible light environment
Existing iris recognition systems are heavily dependent on specific conditions, such as the
distance of image acquisition and the stop-and-stare environment, which require significant …
distance of image acquisition and the stop-and-stare environment, which require significant …
IrisDenseNet: Robust iris segmentation using densely connected fully convolutional networks in the images by visible light and near-infrared light camera sensors
The recent advancements in computer vision have opened new horizons for deploying
biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition …
biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition …
Joint constrained least-square regression with deep convolutional feature for palmprint recognition
Various palmprint recognition methods have been proposed and applied in security,
particularly authentication. However, improving the performance of palmprint recognition …
particularly authentication. However, improving the performance of palmprint recognition …
Deep multi-class eye segmentation for ocular biometrics
Segmentation techniques for ocular biometrics typically focus on finding a single eye region
in the input image at the time. Only limited work has been done on multi-class eye …
in the input image at the time. Only limited work has been done on multi-class eye …
FRED-Net: Fully residual encoder–decoder network for accurate iris segmentation
Iris recognition is now developed enough to recognize a person from a distance. The
process of iris segmentation plays a vital role in maintaining the accuracy of the iris-based …
process of iris segmentation plays a vital role in maintaining the accuracy of the iris-based …