51 citations · 133 across the 20 of their papers we have counts for
18 papers · 1 filter
A Tutorial on ALOS2 SAR Utilization: Dataset Preparation, Self-Supervised Pretraining, and Semantic Segmentation
Nevrez Imamoglu, Ali Caglayan, Toru Kouyama
Masked auto-encoders (MAE) and related approaches have shown promise for satellite imagery, but their application to synthetic aperture radar (SAR) remains limited due to challenge…
Enhanced LULC Segmentation via Lightweight Model Refinements on ALOS-2 SAR Data
Ali Caglayan, Nevrez Imamoglu, Toru Kouyama
This work focuses on national-scale land-use/land-cover (LULC) semantic segmentation using ALOS-2 single-polarization (HH) SAR data over Japan, together with a companion binary wat…
Exploring Object-Aware Attention Guided Frame Association for RGB-D SLAM
Ali Caglayan, Nevrez Imamoglu, Oguzhan Guclu +3
Attention models have recently emerged as a powerful approach, demonstrating significant progress in various fields. Visualization techniques, such as class activation mapping, pro…
Spherical Vision Transformers for Audio-Visual Saliency Prediction in 360-Degree Videos
Mert Cokelek, Halit Ozsoy, Nevrez Imamoglu +4
Omnidirectional videos (ODVs) are redefining viewer experiences in virtual reality (VR) by offering an unprecedented full field-of-view (FOV). This study extends the domain of sali…
SAR-W-MixMAE: SAR Foundation Model Training Using Backscatter Power Weighting
Ali Caglayan, Nevrez Imamoglu, Toru Kouyama
Foundation model approaches such as masked auto-encoders (MAE) or its variations are now being successfully applied to satellite imagery. Most of the ongoing technical validation o…
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features
Enes Karanfil, Nevrez Imamoglu, Erkut Erdem +1
Scene understanding in remote sensing often faces challenges in generating accurate representations for complex environments such as various land use areas or coastal regions, whic…
Spherical Vision Transformer for 360-degree Video Saliency Prediction
Mert Cokelek, Nevrez Imamoglu, Cagri Ozcinar +2
The growing interest in omnidirectional videos (ODVs) that capture the full field-of-view (FOV) has gained 360-degree saliency prediction importance in computer vision. However, pr…
Attention-Guided Lidar Segmentation and Odometry Using Image-to-Point Cloud Saliency Transfer
Guanqun Ding, Nevrez Imamoglu, Ali Caglayan +2
LiDAR odometry estimation and 3D semantic segmentation are crucial for autonomous driving, which has achieved remarkable advances recently. However, these tasks are challenging due…
ST360IQ: No-Reference Omnidirectional Image Quality Assessment with Spherical Vision Transformers
Nafiseh Jabbari Tofighi, Mohamed Hedi Elfkir, Nevrez Imamoglu +3
Omnidirectional images, aka 360 images, can deliver immersive and interactive visual experiences. As their popularity has increased dramatically in recent years, evaluating the qua…
SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks
Guanqun Ding, Nevrez Imamoglu, Ali Caglayan +2
Feed-forward only convolutional neural networks (CNNs) may ignore intrinsic relationships and potential benefits of feedback connections in vision tasks such as saliency detection,…
Exploring Object-Aware Attention Guided Frame Association for RGB-D SLAM
Ali Caglayan, Nevrez Imamoglu, Oguzhan Guclu +4
Deep learning models as an emerging topic have shown great progress in various fields. Especially, visualization tools such as class activation mapping methods provided visual expl…
When CNNs Meet Random RNNs: Towards Multi-Level Analysis for RGB-D Object and Scene Recognition
Ali Caglayan, Nevrez Imamoglu, Ahmet Burak Can +1
Recognizing objects and scenes are two challenging but essential tasks in image understanding. In particular, the use of RGB-D sensors in handling these tasks has emerged as an imp…
Salient object detection on hyperspectral images using features learned from unsupervised segmentation task
Nevrez Imamoglu, Guanqun Ding, Yuming Fang +3
Various saliency detection algorithms from color images have been proposed to mimic eye fixation or attentive object detection response of human observers for the same scenes. Howe…
An Integration of Bottom-up and Top-Down Salient Cues on RGB-D Data: Saliency from Objectness vs. Non-Objectness
Nevrez Imamoglu, Wataru Shimoda, Chi Zhang +4
Bottom-up and top-down visual cues are two types of information that helps the visual saliency models. These salient cues can be from spatial distributions of the features (space-b…
Hyperspectral Image Dataset for Benchmarking on Salient Object Detection
Nevrez Imamoglu, Yu Oishi, Xiaoqiang Zhang +4
Many works have been done on salient object detection using supervised or unsupervised approaches on colour images. Recently, a few studies demonstrated that efficient salient obje…
Solar Power Plant Detection on Multi-Spectral Satellite Imagery using Weakly-Supervised CNN with Feedback Features and m-PCNN Fusion
Nevrez Imamoglu, Motoki Kimura, Hiroki Miyamoto +2
Most of the traditional convolutional neural networks (CNNs) implements bottom-up approach (feed-forward) for image classifications. However, many scientific studies demonstrate th…
Saliency Fusion in Eigenvector Space with Multi-Channel Pulse Coupled Neural Network
Nevrez Imamoglu, Zhixuan Wei, Huangjun Shi +7
Saliency computation has become a popular research field for many applications due to the useful information provided by saliency maps. For a saliency map, local relations around t…
Saliency Detection by Forward and Backward Cues in Deep-CNNs
Nevrez Imamoglu, Chi Zhang, Wataru Shimoda +2
As prior knowledge of objects or object features helps us make relations for similar objects on attentional tasks, pre-trained deep convolutional neural networks (CNNs) can be used…