Russian attacks on the Donetsk and Sumy regions of eastern Ukraine killed at least three people on Monday, Ukrainian authorities said. A Ukrainian drone attack on a car in Russia's Kursk region killed two women, Governor Alexander Khinstein said in a post on Telegram. He said a 53-year-old man was also killed when an explosive device was dropped onto his car. Russian forces destroyed 105 Ukrainian drones overnight, the RIA Novosti news agency reported, citing the Russian Ministry of Defence. Moscow Mayor Sergei Sobyanin said at least 19 Ukrainian drones were destroyed as the capital was targeted for a second night in a row, prompting the closure of all airports for several hours.

Multiple explosions have been heard and a huge fire seen in Port Sudan, though the exact locations and causes were unclear, as Sudan's civil war rocks the previously quiet city for the third day. Dark plumes of smoke could be seen emerging from the vicinity of the country's main maritime port in the city, where hundreds of thousands of displaced people have sought refuge. Al Jazeera's Hiba Morgan, reporting from the Sudanese capital, Khartoum, said residents in the port city reported that attack drones launched by the paramilitary Rapid Support Forces (RSF) hit a fuel depot and other targets. "According to the residents, they believe that it was drone strikes by the paramilitary Rapid Support Forces – once again. They targeted a fuel depot in the city but also around the port and the air base," Morgan said.

This meant that the student network was predicting highly accurate for some burn locations, but not as accurate for others. Some images in burns such as Willamette V alley are more consistent and have a higher temporal resolution than the Sycan Marsh burn. Additionally, some imagery in FLAME 3 contains views of smoke and trees only, and no visible fire in the image. With a three-channel RGB color image only as input, and no distinct fire colors in the image, it may have proven difficult for the student network to segment the fire region. Some of these difficulties are visualized in Figure 3, rows b - e, reflecting not necessarily poor, but not ideal results. In summary, the overall sporadic nature and no visible flames of some of the burn imagery most likely caused lower quantitative IoU for the fire region (Class 1). Sample visual results for a test image from Willamette V alley for the teachers with DeepLabV3+ student network are shown in Figure 4. Table IV shows testing results with different teacher-student variants of the temperature predictions for the ground truth fire region pixels only.

Russia has reported that it repelled a drone attack on Moscow as the capital city prepares to host a major military parade with foreign leaders in attendance. Russia's air defence systems intercepted "four drones flying towards Moscow", Mayor Sergei Sobyanin said on Monday. The attack appears intended to unsettle Moscow's preparations for events marking the end of the Great Patriotic War, commonly known as World War II elsewhere, on May 9. President Vladimir Putin has called for a 72-hour ceasefire to mark the occasion starting on May 8. However, Ukraine has demanded instead a 30-day truce aimed at agreeing to a permanent ceasefire in the conflict that began when Russia invaded in February 2022. Sobyanin said in a post on Telegram that there were no reports of injuries or damage.

Russian forces repelled four drones flying towards Moscow, the capital's mayor, Sergei Sobyanin, said in a post on Telegram. There were no initial reports of damage or casualties, Sobyanin said, adding that emergency services were working at the scene. Ukrainian forces attacked a factory in Russia's Bryansk region, destroying much of the plant, Governor Alexander Bogomaz said on Telegram. There were no casualties, Bogomaz said. Russian forces destroyed 13 Ukrainian drones overnight over Russia's Rostov, Belgorod and Bryansk regions, Moscow's Ministry of Defence said on Sunday.

As the agricultural workforce declines and labor costs rise, robotic yield estimation has become increasingly important. While unmanned ground vehicles (UGVs) are commonly used for indoor farm monitoring, their deployment in greenhouses is often constrained by infrastructure limitations, sensor placement challenges, and operational inefficiencies. To address these issues, we develop a lightweight unmanned aerial vehicle (UAV) equipped with an RGB-D camera, a 3D LiDAR, and an IMU sensor. The UAV employs a LiDAR-inertial odometry algorithm for precise navigation in GNSS-denied environments and utilizes a 3D multi-object tracking algorithm to estimate the count and weight of cherry tomatoes. We evaluate the system using two dataset: one from a harvesting row and another from a growing row. In the harvesting-row dataset, the proposed system achieves 94.4\% counting accuracy and 87.5\% weight estimation accuracy within a 13.2-meter flight completed in 10.5 seconds. For the growing-row dataset, which consists of occluded unripened fruits, we qualitatively analyze tracking performance and highlight future research directions for improving perception in greenhouse with strong occlusions. Our findings demonstrate the potential of UAVs for efficient robotic yield estimation in commercial greenhouses.

Swarming systems, such as for example multi-drone networks, excel at cooperative tasks like monitoring, surveillance, or disaster assistance in critical environments, where autonomous agents make decentralized decisions in order to fulfill team-level objectives in a robust and efficient manner. Unfortunately, team-level coordinated strategies in the wild are vulnerable to data poisoning attacks, resulting in either inaccurate coordination or adversarial behavior among the agents. To address this challenge, we contribute a framework that investigates the effects of such data poisoning attacks, using explainable AI methods. We model the interaction among agents using evolutionary intelligence, where an optimal coalition strategically emerges to perform coordinated tasks. Then, through a rigorous evaluation, the swarm model is systematically poisoned using data manipulation attacks. We showcase the applicability of explainable AI methods to quantify the effects of poisoning on the team strategy and extract footprint characterizations that enable diagnosing. Our findings indicate that when the model is poisoned above 10%, non-optimal strategies resulting in inefficient cooperation can be identified.

Unmanned Aerial Vehicles (UAVs) rely on measurements from Inertial Measurement Units (IMUs) to maintain stable flight. However, IMUs are susceptible to physical attacks, including acoustic resonant and electromagnetic interference attacks, resulting in immediate UAV crashes. Consequently, we introduce a Model-based Anomaly detection and Recovery System (MARS) that enables UAVs to quickly detect adversarial attacks on inertial sensors and achieve dynamic flight recovery. MARS features an attack-resilient state estimator based on the Extended Kalman Filter, which incorporates position, velocity, heading, and rotor speed measurements to reconstruct accurate attitude and angular velocity information for UAV control. Moreover, a statistical anomaly detection system monitors IMU sensor data, raising a system-level alert if an attack is detected. Upon receiving the alert, a multi-stage dynamic flight recovery strategy suspends the ongoing mission, stabilizes the drone in a hovering condition, and then resumes tasks under the resilient control. Experimental results in PX4 software-in-the-loop environments as well as real-world MARS-PX4 autopilot-equipped drones demonstrate the superiority of our approach over existing IMU-defense frameworks, showcasing the ability of the UAVs to survive attacks and complete the missions.

Russian President Vladimir Putin has said that there has so far been no need to use nuclear weapons in Ukraine, expressing "hope" that they will not be required. Putin said his country had enough "strength and means" to bring the three-year war, sparked by Russia's 2022 invasion of Ukraine, to a "logical conclusion with the outcome Russia requires". His comments were part of a documentary marking his quarter century in power by state television channel Rossiya 1 that was released on Sunday. Responding to a question from journalist Pavel Zarubin about the Russian response to Ukrainian strikes on Russian territory, Putin said: "There has been no need to use those [nuclear] weapons … and I hope they will not be required." His comments came ahead of his unilaterally declared three-day ceasefire over May 8-10 to mark the 80th anniversary of the victory of the Soviet Union and its allies over Nazi Germany in World War II, an initiative that he claimed would test Kyiv's readiness for long-term peace.

Sudan's army says the paramilitary Rapid Support Forces (RSF) attacked a military airbase and other facilities in the vicinity of Port Sudan airport. The army said on Sunday that the airbase was targeted using a drone, as well as a cargo warehouse and some civilian facilities, in the first attack in the eastern city by the RSF. There are reports of some damage after drones hit an ammunition depot. "Both the civilian and military airports are in the same place. What we know from residents in the port city is that five drones were launched by the RSF and targeted the airbase," Al Jazeera's Hiba Morgan said, reporting from the capital, Khartoum.