63 citations · 137 across the 14 of their papers we have counts for
15 papers
Mediastinal Lymph Node Detection and Segmentation Using Deep Learning
Al-Akhir Nayan, Boonserm Kijsirikul, Yuji Iwahori
Automatic lymph node (LN) segmentation and detection for cancer staging are critical. In clinical practice, computed tomography (CT) and positron emission tomography (PET) imaging…
Coronavirus disease situation analysis and prediction using machine learning: a study on Bangladeshi population
Al-Akhir Nayan, Boonserm Kijsirikul, Yuji Iwahori
During a pandemic, early prognostication of patient infected rates can reduce the death by ensuring treatment facility and proper resource allocation. In recent months, the number…
High resolution weakly supervised localization architectures for medical images
Konpat Preechakul, Sira Sriswasdi, Boonserm Kijsirikul +1
In medical imaging, Class-Activation Map (CAM) serves as the main explainability tool by pointing to the region of interest. Since the localization accuracy from CAM is constrained…
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting
Pongpisit Thanasutives, Ken-ichi Fukui, Masayuki Numao +1
In this paper, we propose two modified neural networks based on dual path multi-scale fusion networks (SFANet) and SegNet for accurate and efficient crowd counting. Inspired by SFA…
CProp: Adaptive Learning Rate Scaling from Past Gradient Conformity
Konpat Preechakul, Boonserm Kijsirikul
Most optimizers including stochastic gradient descent (SGD) and its adaptive gradient derivatives face the same problem where an effective learning rate during the training is vast…
A Comparative Study of Pretrained Language Models on Thai Social Text Categorization
Thanapapas Horsuwan, Kasidis Kanwatchara, Peerapon Vateekul +1
The ever-growing volume of data of user-generated content on social media provides a nearly unlimited corpus of unlabeled data even in languages where resources are scarce. In this…