This paper reports on an algorithm for automatic, targetless, extrinsic calibration of a lidar and optical camera system based upon the maximization mutual information between sensor‐measured surface intensities. The proposed method is completely data‐driven does not require any fiducial targets—making in situ easy. We calculate Cramér‐Rao lower bound (CRLB) estimated parameter variance, we show experimentally that sample variance parameters empirically approaches CRLB when amount data used...

This paper presents a method for effective ambient light and transmission estimation in underwater images using common convolutional network architecture. The estimated the map are used to dehaze images. Dehazing is especially challenging due unknown significantly varying environments. Unlike dehazing methods, proposed capable of estimating along with thereby improving reconstruction quality dehazed We evaluate performance on real also compare our current state-of-the-art techniques.

p-Nitrophenol (p-NP) is known as a common contaminant found in wastewater, agricultural runoff, and industrial effluents which can degrade water quality cause potential carcinogenic toxic effects on the human body. Its detection essential for public health, safety, environmental protection, regulatory compliance, underscoring its broad applicability. In this study, novel electrochemical sensor based polypyrrole (PPy) flowers assembled via nanotubes was developed sensitive determination of...

We propose a novel and pragmatic framework for traffic scene perception with roadside cameras. The proposed covers full-stack of pipeline infrastructure-assisted autonomous driving, including object detection, localization, tracking, multi-camera information fusion. Unlike previous vision-based frameworks rely upon depth offset or 3D annotation at training, we adopt modular decoupling design introduce landmark-based localization method, where the detection can be well decoupled so that model...

This work presents an extrinsic parameter estimation algorithm between a 3D LIDAR and Projective Camera using marker-less planar target, by exploiting Planar Surface Point to Plane Edge back-projected geometric constraints. The proposed method uses the data collected placing board at different poses in common Field of View (FoV) Camera. steps include, detection target edges frames, matching detected planes lines across both sensing modalities finally solving cost function formed...

This paper presents a challenging multi-agent seasonal dataset collected by fleet of Ford autonomous vehicles at different days and times during 2017-18. The traversed an average route 66 km in Michigan that included mix driving scenarios such as the Detroit Airport, freeways, city-centers, university campus suburban neighbourhoods, etc. Each vehicle used this data collection is Fusion outfitted with Applanix POS-LV GNSS system, four HDL-32E Velodyne 3D-lidar scanners, 6 Point Grey 1.3 MP...

The exponential proliferation of Malware over the past decade has threatened system security across a plethora Internet Things (IoT) devices. Furthermore, improvements in computer architectures to include speculative branching and out-of-order executions have engendered new opportunities for adversaries carry out microarchitectural attacks these Both are imperative threats computing systems, as their behaviors range from stealing sensitive data total failure. With cat-and-mouse game between...

Supercapacitors have gained significant attention for energy storage due to their high power density and long cycle life. In this context, transition metal phosphides are particularly promising electrode materials supercapacitors, owing theoretical capacitance rich redox chemistry. However, they require harsh synthesis conditions prolonged processing time. Herein, a simple, one‐step electrodeposition method is presented the of Fe‐incorporated CoP on Ni foam (NF), offering rapid scalable...

This work presents a novel target-free extrinsic calibration algorithm for 3D Lidar and an IMU pair using Extended Kalman Filter (EKF) which exploits the motion based constraint state update. The steps include, data collection by excitation of Inertial Sensor suite along all degrees freedom, determination inter sensor rotation rotational component aforementioned in least squares optimization framework, finally, translation update framework. We experimentally validate our method collected lab...

This research paper presents an innovative multi-task learning framework that allows concurrent depth estimation and semantic segmentation using a single camera. The proposed approach is based on shared encoder-decoder architecture, which integrates various techniques to improve the accuracy of task without compromising computational efficiency. Additionally, incorporates adversarial training component, employing Wasserstein GAN with critic network, refine model's predictions. thoroughly...

In this paper we perform an extensive experimental evaluation of three planar target based 3D-LIDAR camera calibration algorithms, on a sensor suite consisting multiple 3D-LIDARs and cameras, assessing their robustness to random initialization by using metrics like Mean Line Re-projection Error (MLRE) Factory Stereo Calibration Error. We briefly describe each method provide insights into practical aspects ease data collection. also show the effect noisy result conclude with note which...

This paper reports on a novel two-step algorithm for the estimation of full 6-degree-of-freedom (DOF) [t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> , t xmlns:xlink="http://www.w3.org/1999/xlink">y</sub> xmlns:xlink="http://www.w3.org/1999/xlink">z</sub> θ ] rigid body transformation between any two overlapping point-clouds that have dominant ground plane. We first estimate plane (X-Y plane) from 3D and align them to obtain good...

This paper proposes a deep convolutional neural network (CNN) architecture for automatic classification of mobile laser scanning (MLS) data obtained outdoor environment, which are characterized by noise, clutter, large size and larger quantum information. The developed introduces look up table (LUT) based approach, retains the geometry input MLS point cloud while rescaling. Further, with voxelisation sample, ambiguity selecting one out multiple values within voxel is resolved. performance...

There is a growing need for vehicle positioning information to support Advanced Driver Assistance Systems (ADAS), Connectivity (V2X), and Automated Driving (AD) features. These range from road determination (<5 meters), lane (<1.5 determining where the within (<0.3 meters). This work examines performance of Global Navigation Satellite (GNSS) on 30,000 km North American highways better understand automotive needs it meets today what might be possible in near future with wide area GNSS...

Recently many deep Convolutional Neural Networks (CNN) based architectures have been used for predicting camera pose, though most of these and require quite a lot computing capabilities accurate prediction. For reasons their incorporation in mobile robotics, where there is limit on the amount power computation capabilities, has slow. With mind, we propose real-time CNN architecture which combines low-cost sensors robot with information from images single monocular using an Extended Kalman...