A vehicle perception system converts camera images into brightness and color channels to identify potential construction objects using template matching.
Information processing device segments optical sensing data using map and position information to target object detection models.
A stereo vision camera system switches exposure conditions to capture accurate three-dimensional data and object recognition images.
An information processing apparatus sets labels on scene data to determine storage eligibility.
A steerable landing light system uses a camera and controller to aim illumination along the aircraft's actual travel path.
A feature extraction unit generates modality-independent features from sensor data to enable a single classification unit across multiple input types.
AI models encode image frames to detect blinking vehicle lights, reducing data bandwidth and storage needs.
QPSK beamforming reduces sidelobe energy loss while improving vehicle hazard identification.
Physically-based retrieval converts radiance measurements into labeled training sets, resolving spatial de-correlation issues in land surface classification.
A radar and camera fusion system uses preliminary scanning to identify obstacle types before high-precision tracking.
An end-to-end trained perception model feeds detection outputs into tracking inputs, resolving occlusion-induced data switching errors.
Multi-gate light analysis identifies active emergency vehicles at distance, reducing false positives and collision risk.
A vehicle object recognition method maps sensor clusters to image regions and extracts feature points to calculate movement speed.
A control system adjusts operation limitations on a mobile robot interface based on detected features of nearby individuals.
A misalignment detection unit assesses radar alignment with the vehicle longitudinal direction to adjust signal output conditions.
A multi-sensor fusion method projects millimeter wave radar regions of interest onto camera and lidar feature maps.
Camera-based travel assistance identifies preceding vehicles crossing center lines to generate braking and steering control signals.
A driver assistance system estimates object detection performance using tracking and classification metrics to provide real-time reliability feedback.
A human detection apparatus determines color uniformity in candidate areas to recognize obscured individuals.
A computer-implemented method divides traffic light images into signal portions and determines illumination status using HSV brightness values.
ProtoFac extracts meaningful prototypes from deep neural networks via matrix factorization, replacing internal layers with interpretable weighted concepts.
A hybrid crop health change image combines vegetation index differences with structural similarity measurements to quantify spectral and geometric variations.
A mobile vehicle media display system uses object sensors and neural networks to classify audience entities and compute engagement metrics.
Segmenting environmental data into independent records enables parallel processing within vehicle control units.
A judging unit identifies improper regions using edge patterns to exclude them from target object detection.
A determination reference range changer adjusts detection parameters based on curve direction and relative vehicle position to prevent false alarms.
An information display device generates and projects an avoidance path to guide vehicle navigation around detected obstacles.
A state machine determines target trajectories for autonomous vehicles by evaluating costs against thresholds to navigate around obstacles.
A radar apparatus calculates the locus of representative points to determine object reality.
A photoelectric conversion device uses a control unit to output signals between distinct accumulation periods within a full frame cycle.
Transforming position information into a common coordinate system enables rapid object recognition while reducing bus system load.
A custodianship model distributes tracking functionality across multiple decentralized track fusers.
A vehicle obstacle recognition device calculates an index value to identify objects across multiple sensors.
Retraining a pre-trained generative transformer model with unannotated vehicle sensor data to adapt the system for specific object detection tasks.